Stress-related neural activity (SNA), as measured by amygdala metabolism, has been linked in prior work to all-cause mortality and major adverse cardiovascular events. In this study, we sought to clarify SNA determinants and test whether age modifies its association with all-cause mortality. Using 2-[18 F]fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG-PET), we quantified amygdala metabolism, a surrogate for SNA, in 1,336 patients (mean age 59.4 ± 15.6 years, 37.8% women). Assessing demographic and imaging confounders, associations between SNA and mortality were evaluated in a subgroup of 960 participants with a median 5-year follow-up (IQR 3-9). Higher SNA appears independently associated with greater all-cause mortality across all age groups (HR 1.45, 95% CI 1.08-1.95; p = 0.012). The association is strongest in younger, healthier individuals (HR 7.86, 95% CI 2.92-21.21; p < 0.001) and attenuates with advancing age. Mediation analysis indicates that SNA accounts for 38.2% (95%CI 15.7%-60.7%) of the age-mortality link. Here, we find that SNA is independently associated with all-cause mortality, with effect sizes that diminish with age; if confirmed, incorporating SNA into risk models alongside conventional factors may improve mortality prediction and help identify younger adults, who appear low risk by standard criteria, for closer follow-up and preventive strategies.

Single-molecule localization microscopy enables high-resolution imaging of molecular interactions, but discriminating molecular binding types has traditionally relied on complex strategies, such as multiple dyes, time-division techniques, or kinetic analysis, that are asynchronous, invasive, or time-consuming. Here, we uncover previously overlooked spatiotemporal information embedded within diffraction-limited fluorescence, enabling synchronous classification of individual binding event videos using only a single fluorescent dye. Building on this insight, we propose a Temporal-to-Context Convolutional Neural Network (T2C CNN), which integrates long-term spatial convolutions, shallow cross-connected blocks, and a pooling-free structure to enhance contextual representation while preserving fine-grained temporal features. Applied to DNA-PAINT experiments, T2C CNN achieves up to 94.76% classification accuracy and outperforms state-of-the-art video classification models by 15-25 percentage points. Our approach enables rapid and precise binding-type recognition from fluorescence video data, reducing observation time from minutes to seconds and facilitating high-throughput single-molecule imaging without requiring multiple dye channels or extended kinetic measurements.

It is uncertain how much life expectancy of the Chinese population would improve under current and greater policy targets on lifestyle-based risk factors for chronic diseases and mortality. Here we report a simulation of how improvements in four risk factors, namely smoking, alcohol use, physical activity and diet, could affect mortality. We show that in the ideal scenario, that is, all people who currently smoke quit smoking, excessive alcohol use was reduced to moderate intake, people under 65 increased moderate physical activity by one hour and those aged 65 and older increased by half an hour per day, and all participants ate 200 g more fresh fruits and 50 g more fish/seafood per day, life expectancy at age 30 would increase by 4.83 and 5.39 years for men and women, respectively. In a more moderate risk reduction scenario referred to as the practical scenario, where improvements in each lifestyle factor were approximately halved, the gains in life expectancy at age 30 could be half those of the ideal scenario. However, the possibility to realize these estimates in practise may be influenced by population-wide adherence to lifestyle recommendations.

Prematurity, defined as birth before 37 weeks of gestation, is the leading cause of mortality in children under five, affecting ~11% of live births worldwide (≈15 million annually). Despite advances in neonatal care, preterm infants remain at high risk of complications. In neonatal intensive care units, gastric residuals (GRs) are routinely monitored to guide enteral feeding, yet their microbial composition remains poorly understood. We performed metagenomic sequencing of 199 stool and 69 GR samples from 39 preterm infants during hospitalization to characterize stomach and gut microbiomes. To our knowledge, this is the first metagenomic sequencing of the GR in premature infants. We identified 11 GR microbialclusters, commonly dominated by Staphylococcus, Streptococcus, and Klebsiella, with microbial diversity correlating with aspiration frequency. Colonization was dynamic: early GR samples were enriched with Staphylococcus epidermidis and Bradyrhizobium, while later samples featured Escherichia coli, Staphylococcus hominis, and Streptococcus thermophilus. Stool samples formed eight microbialclusters, frequently enriched with Enterobacteriaceae. S. epidermidis was linked to higher gestational age and lower richness, whereas Bifidobacterium breve, a beneficial commensal, appeared later. Comparative analysis showed overlap between gut and gastric microbiota, with GR samples more dynamic and less subject-specific. Strain-level analysis revealed both individual-specific and widely shared taxa, including a pathogenic Klebsiella aerogenes strain associated with bacteremia, detectable a week before clinical isolation. These findings provide new insights into microbial colonization dynamics of preterm infants.

Heterodimerization of opioid receptors (ORs), MOR, KOR, and DOR, is implied in their functional regulation and diversification, and thus its understanding is crucial for developing better analgesic treatments. However, our knowledge on OR heterodimerization/heterodimers remains limited. Here, using single-molecule imaging and functional analysis, we find that MOR, the main morphine receptor, repeatedly forms transient (≈250 ms) heterodimers with DOR every 1-10 seconds, but not with KOR, whereas DOR and KOR also form transient heterodimers. We obtain all the heterodimer-monomer equilibrium constants and rate constants with/without agonists. We identify the critical heterodimer binding sites in the extracellular domains, in addition to the less-specific transmembrane domains, and develop soluble peptide blockers for MOR-DOR and DOR-KOR heterodimerization, using amino-acid sequences mimicking the extracellular binding sites. With these peptide blockers, we dissect the monomer/dimer roles in OR internalization and signaling. The soluble MOR-DOR heterodimer blocker reduces the development of long-term morphine tolerance in mice.

The ability to rapidly manipulate domain walls in magnetic materials is key to developing novel high-speed spintronic memory and computing devices. Antiferromagnetic materials present a particularly promising platform due to their robustness against stray fields and their potential for exceptional domain wall velocities. Among various proposed driving mechanisms, coherent spin waves could potentially propel antiferromagnetic domain walls to the magnon group velocity while minimizing dissipation from Joule heating. However, experimental realization has remained elusive due to the dual challenges of generating coherent antiferromagnetic spin waves near isolated mobile antiferromagnetic domain walls and simultaneously measuring high-speed domain wall dynamics. Here we experimentally realize an approach where ultrafast laser pulses generate coherent spin waves that drive antiferromagnetic domain walls and develop a technique to directly map the spatiotemporal domain wall dynamics. Using the room-temperature antiferromagnetic insulator Sr2Cu3O4Cl2, we observe antiferromagnetic domain wall motion with record-high velocities up to ~50 km s-1. Remarkably, the direction of domain wall propagation is controllable through both the pump laser helicity and the sign of the domain wall winding number. This bidirectional control can be theoretically explained, and numerically reproduced, by the domain wall dynamics induced by coherent spin waves of the in-plane magnon mode-a phenomenon unique to magnets with an easy-plane anisotropy. Our work uncovers a novel domain wall propulsion mechanism that is generalizable to a wide range of antiferromagnetic materials, unlocking new opportunities for ultrafast coherent antiferromagnetic spintronics.

A defining feature of mycetoma is the presence of grains, which are dense, compact structures composed of the causative bacterial or fungal microorganisms. These grains define clinical resistance to treatment, and the likelihood of chronicity. Understanding the molecular mechanisms underlying grain development are critical for enhancing treatment efficacy; however, important questions remain about the underlying genetic, biochemical, and structural pathways. In this Review, we discuss what is known about mycetoma grain formation, with a focus on Madurella mycetomatis, and the need for multi-disciplinary approaches to aid their clinical management and treatment.

The realization of a quantum computer represents a tremendous scientific and technological challenge due to the extreme fragility of quantum information. The physical support of information, namely the quantum bit or qubit, must at the same time be strongly coupled to other qubits by gates to compute information, and well decoupled from its environment to keep its quantum behavior. An interesting physical system for realizing such qubits are magnetic impurities in semiconductors, such as bismuth donors in silicon. Indeed, spins associated to bismuth donors can reach an extremely long coherence time - of the order of seconds. Yet it is extremely difficult to establish and control efficient gates between these spins. Here we demonstrate a protocol where single bismuth donors can coherently transfer their quantum information to a superconducting flux qubit, which acts as a mediator or quantum bus. This superconducting device allows to connect distant spins on-demand with little impact on their coherent behavior.

Dopant diffusion along grain boundaries (GBs) plays a critical role in modulating the GB chemistry, which further governs the microstructures and properties of polycrystalline materials. Here, we investigate atomistic GB dopant diffusion behaviors by directly tracing GB structures and chemistries in a Ti-diffused Al2O3 GB, using atomic resolution electron microscopy, spectroscopy and theoretical calculations. Our observations unveil that dopant diffusion introduces a GB structural transformation. Furthermore, such structural transformation leads to an unexpected dramatic variation of GB diffusion coefficients for Ti diffusion, which differ by one order of magnitude between the two different GB structures. These findings provide mechanistic insights into the dopant diffusion and segregation phenomena in GBs, providing fundamental understanding towards the intricate nature of GB diffusion processes.